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Lead, Product Designer

Job in New York City, Richmond County, New York, USA
Listing for: Paramount Global
Full Time position
Listed on 2026-08-05
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Engineer
Job Description & How to Apply Below

Lead, Product Designer

CBS Sports isn't just an app; it's the digital stadium for millions of fans. We own the rights and the data that matter—NFL, UEFA Champions League, March Madness, the Masters, and the UFC. When a game is on the line, we are the primary screen in every pocket. But we aren't just a scoreboard. We are a massive content engine of fantasy leagues, brackets, live video, and deep journalism.

We build for the electric atmosphere of a playoff Sunday and the daily ritual of a Tuesday morning trade rumor. We have the scale of a legacy giant and the soul of a startup that's obsessed with what happens when you use AI to build faster than the competition.

About the Role

You'll be a lead designer on a cross-functional squad shipping features across the CBS Sports App for iOS and Android. You'll work directly with a PM and a handful of engineers on problems that show up in the product within weeks, not quarters. The day-to-day is wide. Some weeks you're deep in audience behavior data, pulling analytics directly to understand how fans actually move through the product and where they get stuck.

You'll build user profiles, map out flows, and test concepts directly with fans—sometimes running your own surveys alongside our research team to make sure our strategy is crystal clear. Other days, you're prototyping in an LLM or deep in code, building something interactive to see if an idea actually works ers you're in Figma tightening states, specs, and details with your engineer.

We don't split research, prototyping, and production across different people. You move across all of it.

How We Build (The Builder Culture)

We've moved past the era of endless Jira tickets and slow-motion handoffs. We work in small, cross-functional, tactical squads. Together, you own a problem end-to-end. Fast & Fluid:
We workshop ideas, rough up prototypes, and figure out the smartest way to ship. We're leaning into a hybrid, builder-led process focused on getting interactive, holdable features into the hands of fans as quickly as possible. No Handoffs:
You don't "deliver" designs; you shape the product alongside your team. We value builders with different strengths over specialists who stay in their lane. Craft is a Team Sport:
We crit regularly, post work-in-progress, and expect opinions. Polish is something the whole squad holds.

Your Toolkit: AI + Figma

We are looking for a designer with strong technical intuition who expects AI to be the bedrock of their workflow. You don't need to write production code from scratch, but you do need to be code-confident. You understand the foundational architecture of digital products—how data flows, how repos work, and how logic is structured—well enough to effectively direct AI agents. We design code-first and code-last, and we want someone who is ready to get hands-on.

AI Native:
This isn't a team that's just experimenting with AI tools. We use LLMs to think through problems, stress-test hierarchies, explore edge cases, and draft specs. AI-assisted building is a natural, everyday part of how you design. Rapid Prototyping to Production:
You'll use tools like Cursor or Claude to concept, pull from code repos to iterate directly, and build "holdable" prototypes with real data feeds. When it makes sense, you'll push changes directly into the product with an engineer reviewing. The Canvas for Art Direction:
We view the design canvas (Figma, for now) as a two-way street with code. Since our components are increasingly being built and managed directly in code, we don't use the canvas as just a static library. Instead, it's our free-flowing space for exploration. It's where we sweat the visual details, explore high-polish ideas before bringing them back into the build, and set the specific visual rules that guide our AI tools.

Systems Thinking at Scale:
You bridge the gap between AI and the canvas perfectly. Rather than designing bespoke, one-off screens, you use both toolsets to plan, structure, and generate scalable solutions that hold up across the entire product ecosystem. Internal Tools:
You'll use AI to spin up internal SaaS-style tools that help the squad move faster. If a…

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